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In the highly competitive world that we live in today, its clear to understand that there is a strict competitive market building amongst the great tech companies such as Microsoft, Google, Amazon, Baidu, and other startup companies. All these companies have developed, deployed, and integrated their cloud based solutions with Artificial Intelligence. Artificial intelligence provides the steroids that the Cloud industry needs in order to accelerate its existence, growth, and empowerment. AI has developed key components to help itself with its constant learning processes. These processes can be better understood through “machine learning”. Machine learning allows information to be rapidly digested, conceptualized, and intelligently categorized by artificial intelligence. Cloud products such as Azure from Microsoft, AWS from Amazon, TensorFlow from Google, and more integrate machine learning into their systems to enhance the user experience and make mundane tasks to now be automated with little or no human effort involved.

With this evolution and the stiff competition there can be no collaboration in sight especially from rival companies which have no need to partner up, but to simply dominate their place in the industry. Surprisingly Microsoft and Amazon have done such a collaboration. This collaborated effort is not only to show that larger companies can work together, but also the data collected from this program allows both companies to be more successful in their domination of the cloud space. Microsoft and Amazon have come together to form Gluon. Gluon in the dictionary is defined as a “subatomic particle of a class that is through to bind quarks together”. However, this is not the same Gluon which are referring to. Gluon is the fist distinctive collaborative efforts of these technology giants in the race for Artificial Intelligence and gathering information. Gluon is considered the store-house for machine learning and the ability to “voluntarily” utilize machine learning in the development of products and services by Amazon and Microsoft. This storehouse of technological learning and a knowledge base that is bubbling over with information is the type of data warehouse that AI thrives on.

This cohesive collaboration between developers and machine learning have no blossomed what is dubbed “deep learning”. Deep learning essentially is a combination of three distinct components such as data for training, neural network model, and an algorithm which trains the neural network. The neural network essentially translates the data and feeds AI this information allowing AI to grow on a more diversified scale. This new algorithm that is now being utilized by neural networks self-adjusts its output based on errors in the network output. This is a memory and compute process that machine learning and AI adapts through predictive outputs. An example of deep learning is Caffe2, TensorFlow, Appache MXNet, and Cognitive Toolkit offers options to speed up the neural network which often takes days to compute the data being derived. These products now reduce the learning time and accelerates the parallelization in distributing computation processes.

Even though these products built within Gluon are effective and pose to change the way AI is developing by giving it more knowledge, the key is having developers to utilize these products to diversify and intensify the data stream. AWS has been experimenting with its developers by using MXNet to train the neural networks. Microsoft has become a heavy contributor the open source MXNet by opening it to an ever-increasing rise in developers. The collaboration and data being created and distributed by these two powerhouses with Gluon can be overwhelming for a beginner when first interacting with this program, but even for more advanced developers, the data intensive algorithms seem take a life of its own demanding more ways to conform and adjust with massive error reduction. The four key innovations which is introduced by Gluon are as follows:

Friendly API – using clear and concise code, it allows developers to learn and understand the data.

Dynamic networks – allows for ease of access and the rapid fluctuation of the data structure. Fluency in the data structure is critical for development as it allows hybrid scenarios and reduces stagnancy of the data flow as with previous machine learning software.

Algorithms that devein the network – Seamless combination of the model and algorithm allows the network to adjust definitions during training. This is critical as it allows developers to use programming loops, and conditionals. Algorithms are now easier to change, create, and debug.

High Performance Operators for training – Gives the ability to create dynamic graphs and concise APi without sacrificing speed. Previous versions seemed to have consumed valuable run time that this feature runs through effortlessly and drastically picks up speed.

The question now becomes, how does developers access Gluon? Well its provided through Apache MXNet and the future releases will have support for Microsoft Cognitive Toolkit. The AWS team has already published a front-end interface with low-level API to include other specifications and frameworks. Once accessing Gluon you can utilize an AWS Deep learning AMI to find a plethora of examples and workbooks utilized and documented by fellow developers.

Could this be a taste of what is to come from these super giant tech companies in terms of collaboration in order to leap ahead or is this just an opportunity for the public to advance an already thriving technology called Artificial Intelligence? These tech giants are clearly leveraging all aspects of “free data” and utilizing the voluntary efforts of developers world-wide to feed this neural network. As a partner for Microsoft, we anticipate that Microsoft as being the leader in products on the market will utilize Gluon in order to create more intensive, responsive, and advanced products built with AI as the backbone to reduce many processes and essentially speed up productivity. It Gurus Of Atlanta is your Microsoft partner of choice which brings you the cutting edge in design, technology, and its advancements.

Microsoft and the government has long since been in a battle of the territory as the Microsoft cloud space becomes more viable and the more inexpensive solution for mobility. The Microsoft cloud space has taken off like a rocket in terms of businesses taking advantage of the cloud offerings such as Office 365, Azure, InTune, RMS, Dynamics 365, and more. All these products by Microsoft is giving businesses which were once steadfast and locked into a certain territory due to equipment and its maintenance, now the ability to have a global presence with access to their secured data. This is what Microsoft data centers are, which is essentially the cloud. It eliminates the need for conventional equipment while cutting costs and increasing the availability of the data.

Businesses have gone from whole, full fledged data centers into single standalone data backup solutions with their primary corporate data being housed on Microsoft servers. Microsoft has since boasted the a 99% availability for the data and its assets. To bundle up that high-availability, Microsoft has managed to make its products diverse enough to be used on any computer and innovative enough to where it can be shared, removed, administered, and manipulated with 100% sustainability. By proving this methodology and this products viability, Microsoft has taken a foot hold of the business community worldwide as the entire world is skipping to the beat of the Microsoft Cloud space.

The one entity, and typically is the last component to jump on a popular trend, is the government. Unless the government has a hand in the technology to house their own version of the product or have a secured version of the product that they manage, then they are a bit skeptical to join the band wagon with the rest of the world. For the questions about security and the ability to control or administer the data as per government standards and regulation is the reason Microsoft came up with Azure Government. This Azure space or data center space is specifically and strategically designed for the government to give them the foothold on their data that they require. Various government entities have been making moves towards Azure Government, but it has been a very slow and monotonous process due to the heavy testing and redesigning of certain aspects in order to accommodate the various government department requirements.

Microsoft announced this week to make even more concessions for the government and this is by far one of the greatest. Microsoft announced on Monday that they would allow the government to run Azure Cloud technology on their own servers. This gives the government full control over the cloud space, while being able to utilize Azure full scale with no possibility of the data being housed along with the private sector. Due to hacking possibilities and the security required at government facilities, this gives the government the ease of knowing that they can now utilize the technology without compromising the new currency, which is data!

The utilization of Microsoft Azure in the government space on their servers allows that silo capability that some of these agencies require, such as the military and embassies abroad. These sectors and segments of government will always require their own servers to manage the data being housed. This movement has been confirmed by Microsoft’s head of Global Infrastructure, which is Tom Keane. Tom’s idea is to utilize the Azure Stack in that scenario and make it more attractive to these siloed agencies to expand the reach of Microsoft Cloud technology in the government space.

Due to this move that the cloud space is making, the cloud movement is set to move up a whopping $74.7 billion, which is a 36% increase from 2017. These are the numbers pushed by Canalys due to their research and discovery. Currently out of that increase, Microsoft is set to house at least 14% of that increase in global cloud presence. As the world braces for more innovation from Microsoft and its partners such as IT GURUS OF ATLANTA, Azure Government is set to rapidly grow in the government sector globally. IT GURUS OF ATLANTA will continue to present updates to the Microsoft Cloud space as we are a trusted Microsoft partner of choice.

Facebook is going to create a new news section in its video streaming platform Facebook Watch to feature breaking news stories. The move, which Campbell Brown, the company’s year-old head of news partnerships, announced onstage at the Code Media conference in Huntington Beach, is part of a broader evolution of Facebook’s news strategy. Facebook launched the Watch platform in August as a way to compete more directly with other video distribution platforms online.

The company had created a video tab as early as 2016, but only hosted generic videos that were being shared by friends and family. With Watch, Facebook was trying to own and control original content that it distributes itself exclusively on its own channel.

Competitors like YouTube and Snap also have their own original content, but with Watch and the news focus it’s taking a big step forward.

The social media giant has struggled in recent years to manage the quality of news content that’s being shared on the platform and how news is being consumed by the massive Facebook audience. That said, Campbell continued to recite the Facebook line of self-effacement with the company’s involvement in the media landscape.

“People don’t come to Facebook for news, they come to Facebook for friends and family,” Brown said onstage. While that may be true, much of what friends and family are sharing — especially in this news cycle is news. Facebook is focusing on local news publishers rather than big national outlets to change the conversation and focus on utility of the platform. “I don’t think our focus on false news and integrity morphed into time well spent,” says Adam Mosseri, VP of news feed. “For those set of issues, stuff that violates community standards or false news, those things need to be confronted head on. You have to assume that you’re dealing with an adversary who’s sophisticated and their strategy will change over time, so the work never ends.”

According to Cardiogram founder Brandon Ballinger’s latest clinical study, the Apple Watch can detect diabetes in those previously diagnosed with the disease with an 85 percent accuracy. The study is part of the larger DeepHeart study with Cardiogram and UCSF. This particular study used data from 14,000 Apple Watch users and was able to detect that 462 of them had diabetes by using the Watch’s heart rate sensor, the same type of sensor other fitness bands using Android Wear also integrate into their systems.

In 2015, the Framingham Heart Study showed that resting heart rate and heart rate variability significantly predicted incident diabetes and hypertension. This led to the impetus to use the Watch’s heart rate sensor to see if it could accurately detect a diabetic patient. Previously, Ballinger and his colleagues were able to use Apple’s Watch to detect an abnormal heart rhythm with up to a 97 percent accuracy, sleep apnea with a 90 percent accuracy and hypertension with an 82 percent accuracy when paired with Cardiogram’s AI-based algorithm. Most of these discoveries have been published in clinical journals or abstracts and Ballinger intends to publish the latest findings shortly after presenting at the AAAI 2018 conference this week.

Diabetes is a huge and growing problem in the U.S. More than 100 million U.S. adultsare now living with pre-diabetes or diabetes and more than 1 in 4 of them go undiagnosed, according to the CDC. Part of the problem is the pain that goes into checking blood glucose levels. A patient must prick themselves after every meal and correctly take the right amount of insulin to keep themselves in balance.

Early detection could also help in cutting down on diabetes-related diseases before they get out of hand. While there have been other attempts to build special-purpose glucose-sensing hardware, this is the first large-scale study showing that ordinary heart rate sensors—when paired with an artificial intelligence-based algorithm—can identify diabetes with no extra hardware. So what’s next? Ballinger and his colleague on the study Johnson Hsieh mentioned they could be looking at a number of diseases to detect through heart sensors, possibly even gestational diabetes. Hsieh also cautions that those tested were already known to have diabetes or pre-diabetes and that anyone who thinks they might have it should go to their doctor, not just rely on the Watch to tell them what’s going on.

But the results are promising. We’ll just have to wait and see what else the Apple Watch and other fitness monitors with a built-in heart rate sensor are able to tell us about ourselves next.

Apple customers who like the iPhone X’s facial recognition and edge-to-edge screen but were turned off by the $999 price tag may have additional options at lower prices this fall. Apple is working on a lower-cost iPhone with some of the iPhone X’s best features for a launch later this year, according to Ming-Chi Kuo. The lower-cost iPhone will have the same facial recognition sensor as the iPhone X, as well as an edge-to-edge 6.1-inch LCD screen and no home button. Kuo predicted in a January 23 note it could cost between $700 and $800 — significantly less than the iPhone X, but higher than the current iPhone 8 models. However, KGI Securities says to expect some tradeoffs with the lower-cost iPhone, like the possible inclusion of a single-lens rear camera to save costs. KGI Securities believes it will have an LCD screen, which is an older technology than the OLED screen found in the iPhone X. And Kuo predicts it will have an aluminum casing, which is less premium than the stainless steel on the iPhone X. But the lower price may end up making the new iPhone the best-selling model, with over half of new lineup shipments, KGI Securities predicts.

The low-cost device isn’t the only new iPhone KGI Securities predicts Apple will launch. Apple could be preparing a new version of the iPhone X with better components in the same 5.8-inch sized-body. And there could be a so-called “Plus” version of the iPhone X launched this fall with a massive 6.5-inch OLED screen. Apple typically launches new iPhones in September. The KGI Securities research, which hasn’t been confirmed by Apple, suggests that the company may try to pull a trick that it last tried in 2013. In 2013, Apple tried to introduce a new-lower cost iPhone, called the iPhone 5C, instead of selling the previous year’s model at a discounted price. It was a sales disaster. Apple CEO Tim Cook even admitted that the device sold more poorly than the company expected. Demand for the colorful iPhone “turned out to be different than we thought,” Cook said in 2014.

It seems that Apple may try the iPhone 5C gambit again. KGI Securities predicts that Apple may discontinue the current iPhone X model, instead of selling it at a lower price after the new iPhones come out. The new lower-cost iPhone could help Apple gain market share in China, according to the research, which was also the goal for the iPhone 5C. “Lowering iPhone X’s price after the … new models launch would be a negative to product brand value given 3D sensing and OLED display are features of the new high-price model,” Kuo wrote in a January 22 note. Nikkei reported over the weekend that Apple was slashing iPhone production earlier this week. KGI Securities earlier this month revised its estimate for total iPhone X shipments over its lifetime to 62 million, down from 80 million, in a January 18 research note and said that shipments were “lower-than-expected.” If Apple were to discontinue the iPhone X this year, the lineup this Christmas could look a little bit like this: iPhone “X2 Plus” — Price unknown / iPhone “X2” — $999 and up / iPhone X — discontinued / LCD iPhone with Face ID — $700 to $800 / iPhone 8 or iPhone 8 Plus — $599 or $699 / iPhone SE — $350

You know those ads that seem to follow you to every website? You went to one site one time to check out a thing and bam! that site’s ads now pop up on every site you visit. Well, now Google will let you mute them. At first, it may seem an odd move. Google makes money on its ads business, and giving advertisers free rein to stalk you on every site seems really good for companies hoping to remind you of that thing you checked out one time. But the search giant wrote that it wants to give you, the consumer, more transparency and control. It’s also good for business. Barraging you with reminder ads for the thing you are no longer interested in is not useful for you and is a waste for the business hoping to get you to come back.

Google uses the example of someone looking for snow boots, so we’ll go with that. You look up Snow Boots Co. for some research but decide to go with another type of snow boot not on that site, or just decide you’re no longer interested. That site might still be sending you ads, even though you’re not into them anymore. It’s very annoying to keep seeing everywhere the thing you don’t want. But now you can shut it all down by muting that advertiser. You could already mute ads and adjust ad settings these past few years, but now Google is offering a way for you to mute those pesky reminder ads in a new control in Ad Settings. It also will mute the ad across devices. So if you mute it on your smartphone, Google will mute that ad on your laptop.

It also plans to roll out the new controls on more platforms in the future, like YouTube, Search and Gmail. On top of all that, Google is expanding controls for another unwanted ads feature it implemented in 2012 that allows you to mute ads you don’t want to see anymore. “Millions of people use Mute this Ad on a daily basis, and in 2017, we received more than 5 billion pieces of feedback telling us that you mute ads that aren’t relevant,” Jon Krafcik wrote on the Google post explaining the updates. “We incorporated that feedback by removing 1 million ads from our ad network based on your comments.” Of course, these updates only affect ads rolled out within Google, so you may still see reminder ads from other places. It also can’t get rid of the annoying barrage of ads from your Facebook and Instagram feeds.

The good news is all you have to do to shut down those annoying reminder ads now is go to Google’s Ad Settings to see the ads currently targeting you and hit mute.

It’s been a while since we heard from Snow, the Snapchat clone app in Asia that Facebook once tried to buy, but today the company behind it has scooped up a $50 million investment from SoftBank and Sequoia China. Snow was started by Naver, the Korean firm behind popular messaging app Line, and it had proven popular in Japan, Korea, China and other markets in Asia thanks to a focus on localized filters, stickers and features. Not to mention Snapchat’s famous lack of effort in Asian markets. The Snow app has changed significantly since we last wrote about it, however. It’s no longer a Snap clone.

A major updated that dropped last week removed Snow’s user-to-user communication features and turned it into a dedicated selfie camera app. Without chat, the app doubles down on filters, stickers, augmented reality, and other selfie-related features to make photos and other media that can be exported to social networks or chat groups. Snow users can now, for example, record a video set to music from artists that include Charlie Puth. There’s the usual array of photo filters, alongside a GIF maker and Instagram-like Boomerang feature.

Snow plans to use this new investment to develop its augmented reality and facial recognition technologies. Its App Store listing shows it is working with Chinese unicorn SenseTime on facial recognition. It is also aiming to build partnerships and localize its service in China. Outside of Snow, Snow Corp also owns camera apps Foodie and B612, which it acquired from Line, so they may also be pushed in China as standalone apps, although the tech behind them is also shared with the core Snow app. A Snow representative told TechCrunch that the app now has over 200 million downloads on iOS and Android. The company doesn’t break out specific data for each market, but it said that China is its largest market. In January 2017, we reported that Snow had 40-50 million monthly active users but there’s no further update on the MAU front for now.

SoftBank and Sequoia have bought up 20 percent of the shares of Snow’s China business unit via this deal. Line is among Snow’s other backers, via two investments.

For one thing, it’s setting a higher bar for the YouTube Partner Program, which is what allows publishers to make money through advertising. Previously, they needed 10,000 total views to join the program. Starting today, channels also need to have 1,000 subscribers and 4,000 hours of view time in the past year. In an effort to regain advertisers’ trust, Google is announcing what it says are “tough but necessary” changes to YouTube monetization. For now, those are just requirements to join the program, but Google says it will also start applying them to current partners on February 20.

This might assure marketers that their ads are less likely to run on random, fly-by-night channels, but as Google’s Paul Muret writes, “Of course, size alone is not enough to determine whether a channel is suitable for advertising.” Muret also described changes planned for the more exclusive Google Preferred program, which is supposed to be limited to the best and most popular content. Vlogger Logan Paul was part of Google Preferred until the controversy over his “suicide forest” video got him kicked out last week, a story that suggests some of the limitations to Google’s approach.

Moving forward, Muret said the program will offer “not only … the most popular content on YouTube, but also the most vetted.” That means everything in Google Preferred should be manually curated, with ads only running “on videos that have been verified to meet our ad-friendly guidelines.” Lastly, Muret said YouTube will be introducing a new “three-tier suitability system” in the next few months, aimed at giving marketers more control over the trade-off between running ads in safer environments versus reaching more viewers.

Netflix was the top earning app of 2017 that wasn’t a mobile game, according to Sensor Tower’s new year-end report on the most successful apps and publishers across Apple’s App Store and Google Play. In previous years, the top spot had gone to Spotify, and before that, LINE. But this was Netflix’s year to shine. The service saw gross subscriber revenue of approximately $510 million – a 138 percent increase over last year – per the firm’s estimates. That’s about 2.4 times the $215 million users spent in the Netflix app in 2016. It’s not surprising to see Netflix snagging this top-grossing position. The app has been at the top of the revenue charts at various points throughout 2017. For example, in Q2 Sensor Tower had reported the app saw 233 percent revenue growth year-over-year to $153 million, which was then up from the $46 million it had seen at the same time last year.

At the time, Netflix was reporting a surge in international subscribers, which were accounting for the majority of its new signups. These new users are often joining Netflix through their phone and paying through in-app purchases. By its Q3 2017 earnings reported in October, Netflix had gone on to beat its own expectations for subscriber growth, again thanks to its adoption in international markets. Of the 5.3 million new subscribers in the quarter, 850,000 came from the U.S. while 4.45 million came from international markets. The Netflix app was also the top earner across all of Apple’s App Store. But on Google Play, it ranked below Tiner, Google Drive, LINE, Pandora, and HBO NOW. Another notable app success last year was Tencent Video. In 2016, it was the #14 top grossing app (non-game) by revenue on the App Store alone. This past year, it jumped up to #3 by revenue on the App Store, and #5 in overall revenue across both stores.

In terms of downloads, however, the top app list was dominated by Facebook. This year, Facebook’s main app lost the number one spot to WhatsApp as it sank to #3. Messenger and Instagram followed, and Snapchat was in fifth place. Sensor Tower’s report analyzed mobile games separately. Mixi’s Monster Strike was the top grossing mobile game in 2017 – a position it’s now held for three years in a row. Tencent’s Honor of Kings earned second place, but again, because Google Play isn’t in China. The games list is interesting for other reasons, as well. The one-time hit Pokémon Go didn’t make the top 10, but five year-old Candy Crush Saga did (#5). That goes to show that even though games is largely a hits-based business, it’s possible to have staying power in the market, too.

You might be enjoying the benefits of a credit card with robust rewards today, but odds are when you were first getting started, it was hard to get even close to a card like that. That’s because, for those just getting started or who have a poor credit history, those cards are generally out of reach and a lot of them are, Petal co-founder Jason Gross said. That’s why he and his co-founders looked to start Petal, a service that identifies candidates that would be good credit card holders even if they don’t have a credit history, based on some of their actions rather than just their credit score. The startup said today that it has raised $13 million in a new financing round led by Valar Ventures.

“That has to do with critical changes in the market and access to do with credit post-financial crisis,” Gross said. “The way we think about credit scoring is that it’s sorely outdated; its tech was developed 60 years ago based on a limited subset of financial data that was the only info at the time. It disadvantages certain groups in society in particular. The data that you need to create a more comprehensive score is now available but not being used. When we assembled all those pieces, we felt this was a real problem for millions of people.” Petal’s main product is a credit card, in which qualification for the card is based on the digital record it builds for its users. Rather than just looking at borrowing history, it looks at how much that user makes, spends or saves each month, and looks to offer them more differentiated products like lower interest rates on introductory products. The main goal here is to get people who should be able to responsibly manage a credit card, based on their spending history, actually get one in their hands and start building up that history.

A few of the startup’s most obvious targets are younger audiences that are picking up credit cards and associated products for the first time, as well as those who don’t have access to credit simply because they haven’t had an opportunity to build it. If you’re going to qualify for an important loan down the line say, a mortgage you need to build up that credit history, and that still requires actually getting in the door. “If you look at folks who are thin-file, credit invisible, those who don’t have an accurate score, they’re predominantly young people but they’re disproportionately groups that have historically lacked access to financial services,” Gross said. “Minorities, immigrants, if you lack a score or an accurate score it can cost you very real money throughout your life. Having no score, you’re treated as subprime, you won’t qualify for most financial products, or they’ll be more expensive and inferior.”

Petal isn’t alone in trying to identify good potential candidates for credit cards and getting one into their hands without a robust credit history. There are startups like Deserve, which raised $12 million in October earlier this year. Identifying these potential customers without a credit history is a tantalizing opportunity simply because the credit score might not be the best indicator, but it’s what banks and agencies have to work with for now. Gross hopes that Petal will be able to identify them with their technology and, by doing that, start to build up that big user base.